R: Density of a (conditional) multivariate normal variate

dcmvnorm {MCMCglmm} | R Documentation

## Density of a (conditional) multivariate normal variate

### Description

Density of a (conditional) multivariate normal variate

### Usage

    dcmvnorm(x, mean = 0, V = 1, keep=1, cond=(1:length(x))[-keep], log=FALSE)

### Arguments

`x` | vector of observations
`mean` | vector of means
`V` | covariance matrix
`keep` | vector of integers: observations for which density is required
`cond` | vector of integers: observations to condition on
`log` | if TRUE, density p is given as log(p)

### Value

numeric

### Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

### Examples

    V1<-cbind(c(1,0.5), c(0.5,1))
    dcmvnorm(c(0,2), c(0,0), V=V1, keep=1, cond=2)
    # density of x[1]=0 conditional on x[2]=2 given
    # x ~ MVN(c(0,0), V1)

    dcmvnorm(c(0,2), c(0,0), V=V1, keep=1, cond=NULL)
    # density of x[1]=0 marginal to x[2]
    dnorm(0,0,1)
    # same as univariate density

    V2<-diag(2)
    dcmvnorm(c(0,2), c(0,0), V=V2, keep=1, cond=2)
    # density of x[1]=0 conditional on x[2]=2 given
    # x ~ MVN(c(0,0), V2)
    dnorm(0,0,1)
    # same as univariate density because V2 is diagonal

[Package MCMCglmm version 2.30 Index]